Advances in artificial intelligence in thyroid-associated ophthalmopathy.

Journal: Frontiers in endocrinology
PMID: 38715793

Abstract

Thyroid-associated ophthalmopathy (TAO), also referred to as Graves' ophthalmopathy, is a medical condition wherein ocular complications arise due to autoimmune thyroid illness. The diagnosis of TAO, reliant on imaging, typical ocular symptoms, and abnormalities in thyroid function or thyroid-associated antibodies, is generally graded and staged. In recent years, Artificial intelligence(AI), particularly deep learning(DL) technology, has gained widespread use in the diagnosis and treatment of ophthalmic diseases. This paper presents a discussion on specific studies involving AI, specifically DL, in the context of TAO, highlighting their applications in TAO diagnosis, staging, grading, and treatment decisions. Additionally, it addresses certain limitations in AI research on TAO and potential future directions for the field.

Authors

  • Chenyuan Yi
    Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, China.
  • Geng Niu
    School of Medical Technology and Nursing, Shenzhen Polytechnic University, Shenzhen, China.
  • Yinghuai Zhang
    Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, China.
  • Jing Rao
    Shenzhen Eye Institute, Shenzhen Eye Hospital, Jinan University, Shenzhen, China.
  • Guiqin Liu
    Shenzhen Eye Institute, Shenzhen Eye Hospital, Jinan University, Shenzhen, China.
  • Weihua Yang
    Shenzhen Eye Institute, Shenzhen Eye Hospital, Jinan University, Shenzhen, Guangdong Province, China.
  • XingZhen Fei
    Department of Endocrinology, First People's Hospital of Huzhou, Huzhou University, Huzhou, China.

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